Advances in microprocessor, networking and related technologies have led to wide spread deployment and adoption of server-client based applications. In particular, with the advance of high speed public networks, such as the Internet, increasing amounts of rich content are being served and available for consumption by networked clients. Much of these rich contents are streamed to the client devices for consumption.
While significant advances have been made in networking and related technologies, unless some forms of bandwidth reservation are employed, delivery of content over high speed, best effort networks, such as the Internet, still remains a bit unpredictable, due to varying network conditions.
To minimize the manifestation of these “glitches”, and improve user experience, i.e. continuity, as well as visual and aural fidelity, typically a receiving buffer is employed at the receiving client device to buffer received packets of the content stream and to ensure ample content is available for the decoder of the receiving client device. Moreover, content is encoded for delivery and decoding at different streaming rates (i.e. data rates). In some applications, delivery at a selected one of the streaming/data rates is dynamically adapted based on network conditions, as measured by one or more metrics, such as packet drop rates and so forth.
In practice, deciding when to cue adaptive selection of alternate streaming/data rate based on network conditions has turned out to be a relatively difficult task. Determination has to be made as to what attributes of the distribution quality should be measured, and how they should be measured, to provide the most accurate signal for the adaptation process. Preferably, the solution is scalable, and applies to existing content distribution techniques.
Experience has shown that the various prior art techniques provide acceptable, but not consistently satisfactory performance. Thus, an improved approach to adaptive streaming of content is desired.